Currently, AI Agents are rapidly rising to become key driving forces in the Web3 ecosystem. From automated trading, DeFi analysis, to intelligent governance and data prediction, AI Agents are pushing Web3 towards a more intelligent era. However, AI computing security in decentralized environments still faces significant challenges—how to achieve efficient, secure, and trustworthy AI computing while ensuring data privacy?

This is precisely why Mind Network, with FHE (Fully Homomorphic Encryption) + AI + Web3 at its core, is building the AI computing security infrastructure. As the world's first FHE project to launch on the mainnet, Mind Network is about to welcome its TGE and has become the focus of market attention. So, why is Mind Network's TGE so eye-catching? Let's take a closer look.

Mind Network's core advantages

If a project's visibility is opened up, it certainly has important 'eye-catching points'. However, if a project's TGE is widely noticed, it is certainly because its core advantages have widespread recognition. Mind Network, as the world's first FHE project to launch on the mainnet, has a strong first-mover advantage in the fields of AI computing security and Web3 privacy computing. It has built a complete ecosystem of FHE + AI + Web3 computing and achieved breakthrough progress in data security, AI computing privacy, and decentralized AI Agents collaboration. The fundamental drivers of these advancements are reflected in Mind Network, MindChain, and MindV Hubs.

Mind Network: The leader in the FHE track

As the world's first FHE project to launch on the mainnet, Mind Network is dedicated to building the infrastructure for the HTTPZ era, ensuring data security in Web3 and AI computing. Its technology has achieved significant breakthroughs in FHE algorithm optimization, open-source contributions, and AI computing security.

TFHE-rs v1.0 first deployed: Mind Network was the first to apply ZAMA's TFHE-rs v1.0 codebase to practical scenarios, optimizing the performance and efficiency of FHE computing, making AI computing more efficient when running in an encrypted state.

FHE open-source contributions: Mind Network has open-sourced multiple Rust codebases (FCN, MindChain, Swarms-rust) in the field of FHE and has integrated DeepSeek's official codebase, further solidifying its position as a core contributor in the FHE track.

Infrastructure for the HTTPZ era: Mind Network aims to promote the next generation of zero-trust network protocols (HTTPZ), allowing all decentralized computing to operate in end-to-end encrypted states, laying a technological foundation for AI computing and data security.

MindChain: The core infrastructure for AI computing security

MindChain is the world's first FHE chain designed specifically for AI Agents, providing end-to-end encryption support for AI computing, ensuring data privacy, security, and computational transparency, and has been integrated by multiple AI ecosystem projects.

——DeepSeek (AI inference security): Mind Network collaborates with DeepSeek to ensure the privacy protection of AI computing, allowing AI Agents to perform inference without decrypting data.

——Swarms Shield (Swarm Intelligence security): Mind Network collaborates with Swarms to build a multi-agent (Multi-Agent) secure computing solution, ensuring secure and verifiable interactions between AI Agents.

——World AI Health Hub (medical health data security): Collaborating with ZAMA and InfStones to ensure that medical data remains encrypted throughout the AI computing process.

——AI ecosystem projects such as ai16Z, Virtuals, Spore.fun: These decentralized AI Agents projects have begun to adopt MindChain for enhanced computing security.

I have organized specific use cases based on media reports, which are listed below. Feel free to take a closer look if interested.

Swarms Shield: The decentralized AI computing security system Swarms Shield is an enterprise-level AI security system co-developed by Mind Network and Swarms, focusing on secure communication and computation of multi-agent AI Agents, ensuring fairness, security, and privacy in the execution of AI Agents. Multi-layer encryption: Using AES, SHA, HMAC, and automatic key rotation to ensure end-to-end secure communication between AI Agents. Privacy computing: AI Agents can perform inference and decision-making in FHE encrypted state without decrypting data, avoiding data leakage or attack risks. Swarm Intelligence: Enabling AI Agents to collaborate to achieve consensus computation, ensuring transparent and verifiable execution results.

World AI Health Hub: Medical AI secure computing Mind Network collaborates with ZAMA and InfStones to create the World AI Health Hub, a platform focused on decentralized medical AI computing. The platform guarantees medical data privacy through FHE and promotes the application of AI in health technology. Medical data encrypted computing: AI Agents can perform health predictions, but FHE ensures user data remains encrypted throughout the computing process. Decentralized data consensus: Mind Network blockchain records AI computing results, ensuring data transparency and verifiability, preventing medical AI from being misused or manipulated. Global health AI ecosystem: The goal is to support tens of millions of users and promote a new standard of data security computing in the medical industry. Application process: Users input health data → AI computes health predictions → Computed results remain encrypted → Decrypted after FHE computing consensus, ultimately ensuring user data security.

MindV Hubs: Data security and consensus voting

MindV is a data security and consensus voting solution based on FHE that can help AI Agents expand computing capabilities in a secure environment and improve collaboration efficiency. It serves as a 'plugin system' for decentralized AI computing, allowing AI Agents to flexibly collaborate through external capabilities while ensuring data security.

Main features:

Enhanced AI computing capabilities: AI Agents can expand computing power and security through MindV Hubs; it is suitable for decentralized AI training, data analysis, predictive modeling, and other applications.

Computing power contribution incentives: Users can contribute computing power through MindV Hubs to receive economic incentives while increasing the degree of decentralization in AI computing.

FHE computing + blockchain security + AI task collaboration: Protecting AI data through FHE computing, combined with blockchain to ensure the transparency and decentralization of task execution, ultimately building a distributed AI computing infrastructure.

MindV Hubs elevate the decentralized, secure computing and collaboration capabilities of the AI Agents ecosystem to a new level, providing a more scalable solution for Web3 + AI computing.

Mind + AI: FHE computing security becomes a standard for AI Agents

In AI computing, data is one of the most critical elements; AI Agents need access to user behavior data, transaction records, preference information, and even biometric information to provide intelligent services. However, the transparency characteristic of Web3 means that data on the chain can be viewed by anyone, leading to data privacy issues in AI computing, directly affecting the trustworthiness and usability of AI Agents. Traditional Web3 computing methods, such as zero-knowledge proofs, while protecting data in some scenarios, have high computational costs and limited applications in AI computing and dynamic data analysis. Therefore, AI computing requires a more efficient encrypted computing solution, namely FHE.

Mind Network solves AI computing security issues

Mind Network provides a secure computing solution of FHE + AI + Web3, and its Mind FHE Rust SDK has been integrated by DeepSeek AI, enabling AI Agents to perform inference calculations in a fully encrypted state. This means AI Agents can operate securely in a decentralized environment, whether for trading analysis, medical data computing, or personalized recommendations in decentralized social networks, FHE computing security has become an essential function for AI Agents.

Currently, traditional AI Agents are mostly single-agent models (Single-Agent AI), which run independently, such as automated trading robots, chat AIs, content generation AIs, etc. However, the future trend of AI computing is multi-agent AI (Multi-Agent AI), where multiple AI Agents collaborate to complete complex tasks, such as:

DeFi arbitrage system: Multiple AI Agents collaborate to find the optimal arbitrage path and execute secure transactions.

AI prediction market: Multiple AI Agents collaboratively compute predictive results to form a consensus mechanism.

Swarm Intelligence: Multiple AI Agents collaborate in systems like Swarms Shield to jointly execute complex computational tasks.

However, Multi-Agent AI still faces issues such as computational privacy, data leakage, and unfairness caused by competition among AI Agents. Cases like Mind Network x Swarms Shield provide a security solution of FHE computing + AI Swarm Intelligence, enabling AI Agents to collaborate on consensus computing in a fully encrypted environment, ensuring fairness and security in multi-agent systems. With the successful implementation of Mind Network x Swarms Shield, more people will realize that FHE should become the standard for AI Agents, and Mind Network is poised to become the infrastructure in the field of AI computing security with its leading FHE technology and strong ecosystem.

Valuation potential

Mind Network's positioning is not only as the leader in FHE technology but also as one of the four pillars of AI's future development trends, including:

Data (such as ScaleAI): Driving AI evolution through statistical learning.

Computing power (such as Nvidia): Providing massive computational support for the development of large language models (LLM).

Algorithms (such as DeepSeek / OpenAI): Driving AI Agents towards swarm intelligence and general intelligence.

Security (such as Mind Network): Ensuring AI enters the Trust AI / Practical AI phase, achieving coexistence between AI and humans.

Given Mind Network's core position in the 'security' field, it is evident that the field of AI security is still in its early stages, with enormous growth potential in the future, even expected to rival Nvidia, OpenAI, etc.

Other points worth adding

Airdrop incentives are a common user growth strategy in Web3 projects, and Mind Network cleverly attracts users to participate in ecological construction through CitizenZ Passport+ $vFHE = Airdrop, while also increasing community activity. This strategy can not only attract a vertical user group enthusiastic about airdrops but also indirectly enhance the project's visibility through widespread user participation.

In addition, Mind Network's market expansion plan during the TGE period will also create momentum for it:

Swarms Shield Hub launched: This will further enhance Mind Network's AI computing security ecosystem, attracting more AI projects to join.

World AI Health Hub launched: By expanding the medical AI computing market, Mind Network not only broadened application scenarios but also showcased its technology's practical value in vertical fields. These initiatives have not only brought more attention to TGE but also laid a solid foundation for the project's long-term ecological growth.

While we just talked about technological leadership, Mind Network is not an unselected gem; instead, it has attracted top capital support from Binance Labs, Chainlink, Animoca Brands, and has established partnerships with mature projects like DeepSeek, Swarms, ai16z, Virtuals, etc.

Choosing the right track + technical strength + innovation makes it a key infrastructure for the combination of Web3 and AI. We look forward to seeing if the TGE of a good project in the eyes of large institutions and many seasoned Web3 users really possesses high growth investment value.